DEVELOPMENT OF A GRASSLAND INTEGRITY ... - Springer Link

Environmental Monitoring and Assessment (2006) 118: 125–145 DOI: 10.1007/s10661-006-1237-8

c Springer 2006

DEVELOPMENT OF A GRASSLAND INTEGRITY INDEX BASED ON BREEDING BIRD ASSEMBLAGES BRYAN R. COPPEDGE1,∗ , DAVID M. ENGLE1 , RONALD E. MASTERS2 and MARK S. GREGORY1 1 Rangeland Ecology and Management, Division of Agricultural Sciences and Natural Resources, 368 Agricultural Hall Oklahoma State University, Stillwater, Oklahoma 74078, USA; 2 Tall Timbers Research Station, Tallahassee, Florida (∗ author for correspondence, e-mail: [email protected])

(Received 13 January 2005; accepted 19 July 2005)

Abstract. We utilized landscape and breeding bird assemblage data from three Breeding Bird Survey (BBS) routes sampled from 1965–1995 to develop and test a grassland integrity index (GII) in a mixed-grass prairie area of Oklahoma. The overall study region is extensively fragmented from longterm agricultural activity, and native habitat remnants have been degraded by recent encroachment of woody vegetation, namely eastern redcedar (Juniperus virginiana L.). The 50 individual bird survey points along the BBS routes, known as stops, were used as sample sites. Our process first focused on developing a grassland disturbance index (GDI) as a measure of cumulative landscape disturbances for these sites. The GDI was based on five key landscape variables identified in an earlier species-level study of long-term avian community dynamics: total tree, shrub, and herbaceous vegetation cover indices, overall mean landscape patch size, and grassland patch core size. The GII was then developed based on breeding bird assemblage data. Assemblages were based on commonly used response guilds reflective of five avian life history parameters: foraging mode/location, nesting location, habitat specificity, migratory pattern, and dietary guild. We tested the response of 78 candidate assemblage metrics to the GDI, and eliminated those with no or poor response or with high correlations (redundant), resulting in 13 metrics for use in the final index. Individual metric scores were scaled to fall between 0 and 10, and the cumulative index to range from 0 to 100. Although broader application and refinement are possible, the avian-based GII has an advantage over labor-intensive, habitat-based monitoring in that the GII is derived from readily available long-term BBS data. Therefore, the GII shows promise as an inexpensive tool that could easily be applied over other areas to monitor changes in regional grassland conditions. Keywords: avian assemblages, Conservation Reserve Program, fragmentation, grasslands, juniper, landscape pattern, Oklahoma, response guilds

1. Introduction Habitat fragmentation resulting from decades of human conversion of native grasslands to agricultural landscapes has resulted in major physiognomic changes in the southern Great Plains. A once expansive, almost treeless ecosystem has been transformed into a mosaic of agricultural fields, human settlements, and grassland remnants (Knopf, 1994; Risser et al., 1981; Joern and Keeler, 1995). Ecosystem processes also have been disrupted, as the southern plains are experiencing an

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unprecedented expansion in woody plant populations (Archer, 1994). These expansions are thought to be partially attributable to disruptions in historic natural controls of woody vegetation such as recurrent fire (Bragg and Hulbert, 1976). Other factors, such as intense livestock grazing and elevated atmospheric CO2 levels that favor C3 woody plants (Johnson et al., 1993) are also thought to contribute (Archer, 1994; Brown and Carter, 1998). The existence and integrity of surviving grassland remnants is so threatened by these processes that grasslands are considered among the most endangered ecosystems in North America (Sampson and Knopf, 1994). Recognition of this peril led in part to the establishment of an experimental program to halt or reverse grassland losses while simultaneously benefiting depressed US agro-economies. The Conservation Reserve Program (CRP) was created by the Food Security Act (a.k.a. Farm Bill) in 1985. This program compensates farmers for replacing agricultural efforts on marginal (low-productivity) and highly erodable lands with a cover of perennial vegetation. The overall land management goal of the CRP is to reduce soil erosion, but secondary goals include creation or restoration of wildlife habitat (Dunn et al., 1993). Many subsequent studies have documented the benefits of the CRP for both soil conservation (Burke et al., 1995; Reeder et al., 1998) and local wildlife populations (Johnson and Schwartz, 1993; Hall and Willig, 1994; Best et al., 1997). In fact, Coppedge et al. (2001a) found that cultivated grasslands created by the CRP in Oklahoma may directly benefit imperiled grassland birds in some areas by helping offset habitat losses to encroaching woody junipers. Eastern redcedar (Juniperus virginiana L.) is the primary encroaching woody species in Oklahoma and much of the southern plains, and is spreading at a rate of about 9% annually (Engle et al., 1995). Thus, landscapes of the southern plains are being significantly altered by two simultaneous processes – cropland conversion to cultivated grasslands under the CRP and juniper encroachment of native habitat remnants. Long-term assessment of endemic wildlife response to these processes is critical in evaluating CRP effectiveness, to justify its continuation (Dunn et al., 1993; Ribaudo et al., 2001), and to develop appropriate juniper control strategies to conserve remaining native grassland fragments (Coppedge et al., 2004). Many studies have used the response of avian guilds or assemblages to gauge the severity of landscape change or habitat degradation resulting from human disturbance. Birds are highly mobile and most species are easily detectable, but vary widely in their habitat specificity, making them good indicators of local habitat conditions (Hansen and Urban, 1992; O’Connell et al., 2000). By grouping avian species with similar requirements or responses into ecological assemblages, large-scale landscape conditions can be rapidly assessed for management planning (Verner, 1984). The use of bioindicators was initially developed for aquatic systems based on faunal assemblages such as insects and fish (Karr, 1991; Kerans and Karr, 1994; Karr and Chu, 1999). But numerous examples of avifaunal-based applications in terrestrial ecosystems have been reported in recent studies. O’Connell et al. (1998)

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developed a bird community index to evaluate the biotic integrity of landscapes in the mid-Atlantic highlands region. Allen and O’Connor (2000) used avian guilds to document changes occurring with forest fragmentation from human development around lakes in the northeastern USA. Bryce et al. (2002) used avian assemblages as indicators of riparian habitat conditions affected by human disturbance. Bradford et al. (1998) used bird assemblages as indicators of grazing impacts in Great Basin rangelands, and Browder et al. (2002) used birds as indicators of grassland condition in North Dakota. Thus, avian indices of landscape or habitat condition have been developed in a variety of ecological regions, with the exception of the southern Great Plains. The purpose of this study was to build on these earlier examples by reporting on the initial development of an avian-based index of grassland integrity. This index is based on avian assemblage responses to shifts in agricultural land use (both historically and with recent CRP activities) and juniper encroachment over a 30-year period (1965–1995) in northwestern Oklahoma (Coppedge et al., 2001b).

2. Methods 2.1. STUDY

AREA

The study region was northwestern Oklahoma, USA, an area of predominately mixed-grass prairie, a transition grassland between eastern tallgrass and western shortgrass prairie ecosystems (Risser et al., 1981). Dominant herbaceous species include switchgrass (Panicum virgatum), little bluestem (Schizachyriam scoparium), buffalograss (Buchloe dactyloides), sand bluestem (Andropogon hallii), grama grasses (Bouteloua spp.) and numerous forb species. The region has a continental to sub-humid climate, with mean annual temperatures of 15 ◦ C and mean annual precipitation of 63 cm. Agricultural activities in the region are prominent and include the cultivation of small grains, mostly wheat (Triticum aestivum), and cattle production. Scattered riparian woodlands dominated by cottonwood (Populus deltoides) and upland oak woodlands (Quercus marilandica and Q. stellata) are located in areas of dissected topography. Since 1950, woody plant encroachment by eastern redcedar into remnant grasslands, riparian areas and woodland/grassland ecotones has been notable (Engle et al., 1995). Cultivated (agricultural) grasslands, defined as areas typically dominated by monocultures of non-native pasture grasses and intensively managed to control weeds, have been present at various levels in the study areas since settlement. However, beginning in the late 1980’s, many cropland areas were converted to cultivated grasslands as part of the CRP (Coppedge et al., 2001b). A common practice for CRP enrollments in Oklahoma was the planting of Old World Bluestem (Bothriochloa ischmaeum), a non-native forage species. CRP enrollments are usually not grazed or hayed, and are floristically distinct from native grasslands.

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Figure 1. (a) Locations of 3 Breeding Bird Survey (BBS) routes used within the study region of northwestern Oklahoma in the southern Great Plains of North America (stippled area). Shading within Oklahoma represents areas of major juniper encroachment. (b) Portion of a BBS route illustrating land cover types (detailed descriptions provided in Table I) and fixed ‘stops’, which are 50 ha areas used for annually-repeated point counts of breeding birds and as sampling sites for this study. Modified from figures in Coppedge et al. (2001b) with kind permission of Kluwer Academic Publishers.

Landscapes surrounding 3 Breeding Bird Survey (BBS) routes were used as study areas (Figure 1a). The BBS is an annual roadside survey conducted in late May to early June at over 3000 sites in various habitats across North America (Peterjohn, 1994). The 3 routes used (referred to by their BBS designations) were Eagle City, Tegarden, and Lookout. Located along secondary roads, BBS routes are 39.4 km in length and composed of 50 fixed bird survey points (known as “stops”) located at 0.8 km intervals, where observers conduct 3-min point counts and record all birds seen or heard within a 0.4 km radius (Figure 1b).


2.2. L ANDSCAPE

129

ANALYSIS

Black- and-white aerial photographs taken in 1965, 1981, and 1995 were used to assess landscape changes in relation to agricultural activities and juniper encroachment. Photographs were 61 × 61-cm enlargements at a 1:7,920 scale obtained from the US Department of Agriculture, Aerial Photography Field Office, Salt Lake City, Utah. Portions of photographs covering BBS survey areas were delineated as polygons on acetate overlays, digitized, and processed using LTPlus v2.2 software produced by the US Forest Service. Corrected images were exported into the Geographic Information System (GIS) ARC/INFO (ESRI Inc., Redlands, California). Separate vector images were joined to form a complete geo-registered landscape image for each stop for each date, resulting in 450 sampled sites (3 routes × 50 stops each × 3 photography dates). Photo-interpretation involved identifying landscape features and assigning land use/vegetation cover types to all polygons using a classification scheme following Coppedge et al. (2001a). The 11 cover types fell into 2 general categories: those of natural vegetation cover or areas of anthropogenic and miscellaneous land cover (Figure 1b and Table I). Native and cultivated grasslands were distinguished by the

TABLE I Descriptions of major land cover types used to classify habitat polygons in landscapes of northwestern Oklahoma, 1965–1995 Land cover type

Description

Natural vegetation cover types Juniper woodland Wooded areas with >60% woody cover of Juniperus spp. Mixed woodland Wooded areas with approximately equal juniper and deciduous composition and total woody cover >60%. Deciduous woodland Wooded areas with >60% woody cover of deciduous species such as Quercus and Populus. Shrubland Areas with >50% cover of short-statured woody perennials such as Rhus, Artemisia, and Prunus spp. Native grassland Areas dominated by native herbaceous perennial grasses. Anthropogenic/miscellaneous cover types Cultivated grassland Land used for grazing; dominated by introduced forage grasses such as Cynodon, Eragrostis or Bothriochloa spp. Many are the result of CRP enrollments Cropland Annually cultivated agricultural areas. Bare ground Water Roads Developed areas Includes residential areas, commercial areas, and cemeteries.

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presence or absence of linear features indicative of previous mechanical manipulation associated with cultivation, such as terracing and plow furrows, as well as color, density, uniformity, and heterogeneity characteristic of a monoculture or area subject to weed control (Coppedge et al., 2001b). Polygon classification was verified by ground-truthing the 1995 photography. Polygons with natural vegetation were further assigned canopy cover class values for four vegetation components: juniper tree cover, deciduous tree cover, shrub cover, and herbaceous cover. For each site, an area-weighted index was calculated for each of the four types of vegetative cover following the methods of Coppedge et al. (2001a). A fifth index, total woody cover, was derived by summing juniper and deciduous indices, as this particular measure was shown to be an important variable in explaining avian community dynamics in an earlier species-level study (Coppedge et al., 2001a). Imagery was also subjected to landscape pattern analysis with FRAGSTATS v2.0 (McGarigal and Marks, 1995). For this analysis, we calculated mean patch size (ha) and mean native grassland patch core size (ha) for each site, as both of these variables were identified as important in an earlier study (Coppedge et al., 2001a). A patch core is the portion of a patch interior lying a specified distance away from the patch boundary and is presumably free of any edge-related effects or influences (Gustafson, 1998). For our study, we applied a 100-m buffer to derive patch core sizes.

2.3. G RASSLAND

DISTURBANCE INDEX ( GDI ) DEVELOPMENT

We began by developing a grassland disturbance index (GDI). This habitat-based index provides separate validation for the desired avifaunal index, and allows comparisons to studies strictly documenting landscape structural dynamics (Coppedge et al., 2001b). Most importantly, the GDI was used to screen the large number of avian community variables available and select variables for further analysis (Section 2.5. below). Five landscape variables were used to develop the GDI: total tree, shrub, and herbaceous vegetation cover indices, mean patch size, and mean native grassland patch core size. We first examined a frequency distribution of these 5 variables to determine their 80, 60, 40 and 20th percentiles to use as a basis for assigning ranks reflecting grassland disturbance severity. High herbaceous cover and large mean patch and core sizes would be indicative of minimal disturbance (Coppedge et al., 2001b). Therefore, the highest percentile (80–100) of these variables received a rank of five while the lowest (0–20) a rank of one. Rank assignments were reversed for tree and shrub cover indices as higher numbers for these variables indicate more severe grassland disturbance from encroaching woody vegetation. The mean of these five assigned ranks was multiplied by 20 to create an intermediate composite score scaled between 20 and 100. The frequency distribution of this composite score was examined to identify natural breaks in the distribution, resulting in a gradient of six disturbance categories (Table II).

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TABLE II Summary of landscape variables used for classification of sampled sites into a grassland disturbance index (GDI), a general measure of cumulative landscape disturbance GDI level means (SE) Variable

1

2

3

4

5

6

Vegetation cover indices Total tree 3.02 (0.30) 2.83 (0.36) 3.63 (0.37) 8.45 (0.59) 17.11 (1.10) 29.65 (2.02) Shrub 2.49 (0.48) 2.85 (0.44) 3.67 (0.44) 5.48 (0.50) 6.14 (0.57) 10.33 (1.03) Herbaceous 64.69 (2.70) 38.30 (3.32) 38.68 (2.80) 40.56 (1.96) 37.71 (1.55) 28.49 (1.93) Landscape pattern/structure Mean patch 5.42 (0.28) 5.22 (0.39) 3.20 (0.11) 2.57 (0.08) 2.02 (0.06) 1.82 (0.08) size (ha) Grassland patch 3.68 (0.33) 1.33 (0.20) 0.45 (0.08) 0.36 (0.05) 0.10 (0.02) 0.02 (0.01) core size (ha)

2.4. A VIAN

ASSEMBLAGE DATA

Because of annual variations in bird abundance and BBS methodological limitations, we followed general recommendations (Geissler and Noon, 1981) and previous examples (Brennan and Schnell, 2005) for analyzing BBS data by utilizing mean counts for each site derived from a 5-year window of time centered around the dates of aerial photography. Mean abundance per site per date (1965, 1981, and 1995) was calculated for 59 breeding bird species, which included all members of the Passeriformes (perching birds), Piciformes (woodpeckers), Cuculiformes (cuckoos and roadrunners), Columbiformes (doves) and Apodiformes (swifts and hummingbirds). Numerous guild classification schemes exist, based on a variety of factors such as foraging techniques (DeGraaf et al., 1985), migratory patterns, trophic level, etc. (Croonquist and Brooks, 1991). We sought to utilize response guilds descriptive of a variety of aspects of avian life history and ecological requirements (Hansen and Urban, 1992) and those useful for potential management planning activities (Verner, 1984). Assemblages used were based on five non-exclusive guild categories reflecting different ecological foci (see Appendix A for details of species assignments). Foraging mode/location. Breeding season foraging techniques and locations derived from DeGraaf et al. (1985) served as a basis for assigning species to one of four guilds within this category: aerial, canopy, bark/bole, or ground/low shrub foragers. Nesting location. Preferential nesting habits from Ehrlich et al. (1988) was the basis for the four guilds in this category: canopy/structural (which included bridges, culverts, buildings, etc.), cavity, ground/low shrub, or brood parasite. As only one

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species (the Brown-headed Cowbird – Molothrus ater) constituted the latter guild, we hereafter refer to this guild only as the Brown-headed Cowbird. Habitat specificity. Information from several sources was combined to designate four guilds within this category. Grassland obligates and facultative species were derived from lists provided by Vickery et al. (1999). Woodland birds were derived from Peterjohn and Sauer (1994). Remaining species were primarily assigned to an edge habitat guild based on information in DeGraaf et al. (1991) and our knowledge of local species habitat preferences. Migratory pattern. Species were assigned to one of four guilds within this category based on Ehrlich et al. (1988): residents (year-round), temperate migrants, neotropical migrants, or exotics (non-native species). Dietary. Dietary guild assignments were made based on breeding season information contained in DeGraaf et al. (1985) and were as follows: insectivores, granivores, carnivores, and omnivores. 2.5. GRASSLAND

INTEGRITY INDEX ( GII ) DEVELOPMENT

Our general approach to GII development followed that of Bryce et al. (2002). In preliminary analysis, a sampled site identified as lacking any relevant breeding bird data was deleted, leaving a dataset containing 449 sites. To develop the GII, we split this dataset in two halves, using data from half of the sites (even-numbered BBS stops) for developing the GII, and data from the remaining sites (odd-numbered BBS stops) for testing the applicability of the technique. Due to the linear nature of BBS routes and their adjacent stops, spatial autocorrelation of bird data was a concern. Although not consistent for every species, earlier work has detected autocorrelation in this BBS data (Coppedge et al., 2004). The extent of spatial autocorrelation for each assemblage was examined by calculating Moran’s I using GS+ software (Robertson, 1998). We used the distance between stops (0.8-km) as the first lag distance, 1.6-km for the second lag interval, and continued by increasing lag distance by 0.8-km. By examining an autocorrelogram constructed by plotting I against lag distance, we were able to visually detect autocorrelation. None was detected for any assemblage metric (detailed below). Thus, we are confident that autocorrelation concerns were adequately addressed, especially when adjacent sites (odd vs. even-numbered BBS stops) were used in separate development and testing phases. We began GII development with a pool of 78 candidate metrics tested for their response to the GDI. For most of the 20 avian assemblages, a quartet of metrics was used: number of individuals, number of species, percentage of individuals, and percentage of species. Two assemblages, the Brown-headed Cowbird and carnivore, were comprised of only a single species each, so only the number and percentage of individuals metrics were testable. Two additional variables, total abundance and species richness, were also tested against the GDI. For each metric, scores from each site were plotted against and correlated with GDI scores. To be retained, a metric had to exhibit a significant response, either

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positive or negative, to the GDI. To further reduce the number of candidate metrics, a 78 × 78 correlation matrix was examined to identify highly correlated metrics. Once a final set of 13 metrics was chosen, each metric with a negative response was scored on a continuous scale of 0 to 10. A metric score was calculated by dividing the raw metric score by its range and multiplying by 10. The range was defined as the lowest possible (0) to highest recorded value in the dataset. Some metrics also exhibited a positive response to the GDI. For these metrics we reversed the scoring, making them range from 10 to 0. The GII was calculated as the sum of the metric scores divided by 13 and multiplied by 10 to put them on a scale of 0 to 100. We then used correlation analysis to compare GDI and GII scores.

3. Results 3.1. GRASSLAND

DISTURBANCE INDEX ( GDI )

A GDI category designation of one was assigned to sites with the least amount of disturbance and six to sites with severe disturbance (Table III). As the GDI was designed to do, sites with the highest relative amount of tree and shrub cover concurrent with the lowest herbaceous cover, patch and core sizes were identified as the most severely disturbed. Mean patch size in these severely disturbed sites was TABLE III Examples of GDI ranking and scoring technique for the least and most disturbed sites Site and landscape variable Least disturbed site Total tree cover index Shrub cover index Herbaceous cover index Mean patch size Native grassland patch core size Mean rank Most disturbed site Total tree cover index Shrub cover index Herbaceous cover index Mean patch size Native grassland patch core size Mean rank

Observed value

Percentile

Rank

1.4 0.7 48.4 10.0 7.8

(0–20) (0–20) (60–79) (80–100) (80–100)

5 5 4 5 5 4.8 (×20)

31.3 11.1 15.7 2.0 0.0

(80–100) (80–100) (0–20) (20–39) (0–20)

Intermediate composite score

GDI category

96

1

24

6

1 1 1 2 1 1.2 (×20)

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Figure 2. Temporal dynamics of the study region of northwestern Oklahoma from 1965 to 1995 resulting from site classification by the grassland disturbance index (GDI).

less than 2 ha, as compared with the minimally disturbed sites with a mean of over 5 ha (Table II). Grassland patch core size differences were also notable, ranging from 0.02 ha in severely disturbed sites to nearly 4 ha in minimally disturbed sites (Table II). Landscape dynamics were examined by grouping sites according to the year sampled. In 1965, 19 and 7% of sites fell into the two most severely disturbed categories (5 and 6) respectively, and 12% into the minimally disturbed category (1) (Figure 2). By 1995, minimally disturbed sites had decreased to 9% of the total, but disturbance classes 5 and 6 had increased to 26 and 9% of the total, respectively (Figure 2). 3.2. G RASSLAND

INTEGRITY INDEX ( GII )

Out of 78 avian assemblage metrics tested against the GDI, 50 showed a significant response. However, after examining a 78×78 correlation matrix for redundancy, the number retained for use in GII development was reduced to 13 (Table IV). Metrics from 8 separate assemblages showed a positive response to the GDI with correlation coefficients (r) ranging from 0.148 to 0.463 (all P < 0.05): canopy foragers, ground/low shrub foragers, canopy/structural nesters, cavity nesters, edge species, woodland species, residents, and omnivores (Table IV). Metrics from 5 other assemblages exhibited a negative response to the GDI, with coefficients ranging from −0.222 to −0.373 (all P < 0.05): aerial foragers, grassland obligates, temperate migrants, neotropical migrants, and insectivores (Table IV). Several pairs of metrics from within particular guild categories also showed interesting visual relationships


TABLE IV Results of correlation analysis of breeding bird assemblage metrics against the grassland disturbance index (GDI) Assemblage category

Responsive metricsa (r)

Total abundance Species richness Foraging mode/location Aerial foragers Canopy foragers Bark/bole foragers Ground/low shrub foragers Nesting location Canopy/structural nesters Cavity nesters Ground/low shrub nesters Brown-headed cowbird Habitat specificity Grassland obligates Grassland facultatives Edge species Woodland species Migratory pattern Residents Temperate migrants Neotropical migrants Exotic species Dietary Insectivores Granivores Carnivore Omnivores

none 1 1, 3, 4(−0.222) 1, 2(0.302), 3, 4 1, 2, 3, 4 2(0.148) 2, 3(0.183) 1, 2(0.307), 3, 4 1, 3, 4 none 1, 2, 3(−0.373), 4 none 2, 3(0.220), 4 1(0.374), 2, 3, 4 1,2,3(0.463), 4 1, 3(−0.271), 4 1, 3, 4(−0.228) none 1, 2, 3(−0.275) none none 1, 2, 3(0.308), 4

Of the 78 metrics tested, 50 showed a significant (P < 0.05) response to GDI. The 13 metrics underlined and followed by their respective Pearson correlation coefficient (r) were those least redundant with other metrics and were retained for use in the subsequent development of the grassland integrity index (GII). a For each assemblage (except total abundance, species richness, Brown-headed cowbirds and carnivores) four metrics were tested: number of individuals, number of species, percentage of individuals and percentage of species (labeled as 1, 2, 3 or 4 respectively in the column above). As the Brown-headed cowbird and carnivore were single-species assemblages, only the number and percentage of individuals metrics (1 and 3) could be tested.

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with the GDI that contrasted one another. For example, residents increased notably with disturbances classifications, while both types of migrants, when pooled, showed substantial decline in response to disturbance (Figure 3). Similarly, omnivores respond positively to disturbance, while insectivores did not (Figure 4). GII scores for the 224 sites sampled between 1965 and 1995 that were used for developing the index ranged from 25.2 to 96.6 (Table V). GII scores for these sites was negatively correlated with their corresponding GDI scores (r = −0.472; P < 0.001), as the 2 indices were designed as contrasting measures of landscape condition. To test the GII technique, we then applied the scoring process to the remaining portion of the dataset comprised of landscape and avian assemblage data from 225

Figure 3. Responses of resident and migrant (temperate and Neotropical combined) assemblages to the grassland disturbance index (GDI) site classification based on data from 1965 to 1995.

Figure 4. Responses of omniovore and insectivore assemblages to the grassland disturbance index (GDI) site classification based on data from 1965 to 1995.


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TABLE V Examples of GII scoring technique for the highest scoring site

Metric % of aerial foraging spp.

Observed value

Range or scoring criteria

Metric score

50

50

10.0

No. of canopy foraging spp.

0

6

10.0

No. of ground/low shrub foraging spp. % of canopy nesting individuals No. of cavity nesting spp.

1

15

9.3

4

100

9.6

0

8

10.0

96

100

9.6

% of grassland obligate individuals % of edge habitat individuals No. of woodland habitat individuals % of resident individuals % of temperate migrant individuals % of neotropical migrant spp. % of insectivorous individuals % of omnivorous individuals Sum of metric scores

0

93.1

10.0

0

3.4

10.0

0

86.8

10.0

96 50 100 0

100 66.7 100 88.9

9.6 7.5 10.0 10.0 125.6

Comments Scoring criteria = highest observed value. Reverse metric scored on a 10–0 number line. Reverse metric scored on a 10–0 number line. Reverse metric scored on a 10–0 number line. Reverse metric scored on a 10–0 number line. Scoring criteria = highest observed value. Reverse metric scored on a 10–0 number line. Reverse metric scored on a 10–0 number line. Reverse metric scored on a 10–0 number line. Scoring criteria = highest observed value. Scoring criteria = highest observed value. Scoring criteria = highest observed value. Reverse metric scored on a 10–0 number line. To scale the GII to fall between 0 and 100, the sum of the metric scores (125.6) was divided by 13 and multiplied by 10 yield a score of 96.6 for the site

sites set aside for this purpose. This data had not been previously plotted against or correlated with GDI scores. We used the same 13 metrics chosen from the initial technique development, adjusting only the range or scoring criteria (as demonstrated in Table V) to reflect those values present in the test data. GII scores for these test sites was also negatively and significantly correlated with their corresponding GDI scores (r = −0.429; P < 0.001).

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4. Discussion We developed a grassland integrity index (GII) based on multiple avian assemblages and their response to the a priori measure of landscape disturbance and condition (the GDI). In western US rangelands, Bradford et al. (1998) used avian assemblages to assess the degree of rangeland degradation resulting from various levels of livestock grazing. However, their efforts were somewhat hampered by the low species diversity of the potential avifauna. Great Plains avifaunas are also notably depauperate (Wiens, 1974; Knopf, 1986); for example, our grassland obligate assemblage consisted of only 6 species (Appendix A). Thus, we were initially concerned about applying a guild-based process to a grassland situation since limited avifaunal diversity might hamper the detection of suitable avian indicators. But as our results show, our approach, modeled after a technique developed for riparian areas (Bryce et al., 2002), served successfully as the basis for developing an index of grassland integrity. Our study represents only the second time grassland birds have been used as bioindicators of grassland condition (Browder et al., 2002) despite the widely recognized and precipitous decline in this particular group (Peterjohn and Sauer, 1999). Furthermore, our guild-based approach, as compared to the species-level methodology of Browder et al. (2002), produced comparable results. Thus, it would seem prudent, in light of the success of both techniques, for future efforts to undertake comparative studies to determine what level of avifaunal data might provide the most reliable and consistent results for long-term grassland monitoring. Many studies have provided compelling evidence to support the idea that disturbance, in the form of habitat destruction, fragmentation, or degradation, either alone or collectively, are key processes behind the decline of grassland obligate birds specifically and migratory species in general (Maurer and Heywood, 1993; Murphy, 2003; Peterjohn and Sauer, 1999; Robbins et al., 1989). Previous studies in a variety of habitat types have shown that disturbance by fragmentation generally leads to increases in avian generalists or “disturbance-tolerant” species at the expense of more sensitive species (Saab, 1999; Canterbury et al., 2000; O’Connell et al., 2000). Grassland degradation, as measured by our GDI, was accompanied by increases in avian generalists such as omnivores and residents, while insectivores and migratory species declined (Figures 3 and 4). A disturbance-driven shift in dietary guilds from dominance by a specialized insectivorous community to one characterized by generalist omnivores is consistent with reports from earlier studies (O’Connell et al., 1998; Bryce et al., 2002). A possible contributing cause for the particular shift we observed was provided by a related study from the same area, which documented invertebrate biomass levels that were almost 3 times higher on native grasslands than on CRP fields planted with Old World Bluestem (Chapman, 2000). We also found that migratory species (temperate and neotropical groups combined), as opposed to residents, decline with increasing levels of disturbance (Figure 4). Transition in prevalence from migrants to residents and especially the


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unique sensitivity of Neotropical migrants to disturbance have also been reported previously (Flather and Sauer, 1996; Tankersley, 2004). Interestingly, another related study found that abundance of many overwintering passerines known to feed on juniper fruit increased concomitantly with juniper encroachment in Oklahoma (Coppedge et al., 2001c). Not surprisingly, many of these species are also year-round residents. Thus, cumulative long-term disturbance is clearly linked to fundamental changes in the trophic structure of the grassland avian community in the study area (Coppedge et al., 2001a). Shifting agricultural activities and land cover changes are significant to longterm grassland bird population dynamics (Murphy, 2003). Results of this and related studies (Coppedge et al., 2001a, 2004) also suggest that increasing woody vegetation drives dramatic changes in avian community structure and composition in grasslands as well. Not only do many specialized assemblages such as grassland obligates, temperate and neotropical migrants and insectivores decrease with increasing GDI site classifications, but notable increases are seen in several generalist and woodland-associated assemblages. For example, increasing numbers of cavitynesting and woodland species in Great Plains grasslands are clear demonstrations as to the extent woody vegetation has modified grassland habitat and associated bird communities (Knopf, 1986, 1994; Coppedge et al., 2001a). The expansion of woody vegetation along major rivers in the central Great Plains has long been known to provide breeding habitat for North American forest species with eastern geographic affinities, allowing them to expand westward (Knopf, 1986, 1994). We are now seeing evidence of a similar phenomenon in non-riparian, upland grassland habitats as a result of juniper encroachment, with serious implications for future grassland conservation efforts (Coppedge et al., 2004). One of the strengths in the methodology we adapted from Bryce et al. (2002) is that a broad variety of response guilds are represented in the final index. This is important in detecting small shifts in the avian community in response to subtle and cumulative landscape changes (Croonquist and Brooks, 1991). As has been shown by Cully and Winter (2000), woody vegetation accumulation in grasslands hampers bird community delineation in long-term monitoring as the boundaries between habitat types often becomes blurred over time. The GII distinguishes categories along a broad disturbance gradient fairly well. The GII may overcome the problem of transitioning habitats as it is faunal-based and also uses long-term BBS data as other recent grassland assessment and monitoring studies have done (Browder et al., 2002; Brennan and Schnell, 2005). It may also detect areas in intermediate condition that otherwise may be difficult to distinguish with other monitoring tools such as remote sensing technology (Cully and Winter, 2000). The variables used to create the GDI were selected from a previous species-level avian study (Coppedge et al., 2001a) and are certainly not the only landscape variables to which avian assemblages might respond. Future efforts will focus on refining the GII and broadening its’ practical application to other regional grassland areas covered by the BBS.

Columbiformes Rock Dove Mourning Dove Cuculiformes Black-billed Cuckoo Yellow-billed Cuckoo Greater Roadrunner Apodiformes Chimney Swift Piciformes Red-headed Woodpecker Red-bellied Woodpecker Downy Woodpecker Hairy Woodpecker Northern Flicker Passeriformes Eastern Phoebe Great Crested Flycatcher Western Kingbird Eastern Kingbird Scissor-tailed Flycatcher

Species G G C C G A B B B B G A A A A A

Columba livia Zenaida macroura Coccyzus erythropthalmus Coccyzus americanus Geococcyx californianus Chaetura pelagica Melanerpes erythrocephalus Melanerpes carolinus Picoides pubescens Picoides villosus Colaptes auratus Sayornis phoebe Myiarchus crinitus Tyrannus verticalis Tyrannus tyrannus Tyrannus forficatus

Foraging

C V C C C

V V V V V

C

C C G

C C

Nesting

E W F F F

W W W W E

E

W W E

E F

Habitat

I I I I I

I I I I I

I

I I I

O G

Dietary

(Continued on next page)

T N N N N

R R R R R

N

N N R

X T

Migratory

Assemblage category

APPENDIX A Breeding bird species and their respective assemblage memberships used for analysis

140 B. R. COPPEDGE ET AL.

Loggerhead Shrike Warbling Vireo Blue Jay American Crow Horned Lark Purple Martin Northern Rough-winged Swallow Cliff Swallow Barn Swallow Carolina Chickadee Black-capped Chickadee Tufted Titmouse Carolina Wren Bewick’s Wren House Wren Blue-Gray Gnatcatcher Eastern Bluebird American Robin Gray Catbird Northern Mockingbird Brown Thrasher European Starling Cassin’s Sparrow

Species Lanius ludovicianus Vireo gilvus Cyanocitta cristata Corvus brachyrhynchos Eremophila alpestris Progne subis Stelgidopteryx serripennis Petrochelidon pyrrhonota Hirundo rustica Poecile carolinensis Poecile atricapilla Baeolophus bicolor Thryothorus ludovicianus Thryomanes bewickii Troglodytes aedon Polioptila caerulea Sialia sialis Turdus migratorius Dumetella carolinensis Mimus polyglottos Toxostoma rufum Sturnus vulgaris Aimophila cassinii G C G G G A A A A C C C C G C C G G G G G G G

Foraging

APPENDIX A (Continued)

C C C C G V V C C V V V V V V C V C C C G V G

Nesting F W W E O E E E E W W W E E E E F E E E E E O

Habitat C I O O O I I I I I I I I I I I I O O O O O I

Dietary

(Continued on next page)

T N R R T N N N N R R R R R T N R T N R T X T

Migratory

Assemblage category


141

Spizella pusilla Chondestes grammacus Ammodramus savannarum Cardinalis cardinalis Passerina caerulea Passerina cyanea Passerina ciris Spiza americana Agelaius phoeniceus Sturnella magna Sturnella neglecta Xanthocephalus xanthocephalus Euphagus cyanocephalus Quiscalus quiscula Quiscalus mexicanus Molothrus ater Icterus spurius Icterus galbula Carduelis tristis Passer domesticus G G G G G C C G G G G G G G G G C C C G

Foraging G G G C C C C G C G G C C C C B C C C V

Nesting E F O E E E E O F O O E F E E F E E E E

Habitat R T T R N N N N T T T T T R R T N N T X

Migratory

Assemblage category

O O O O O O O O O I I O O O O O I O O G

Dietary

Assemblage categories are as follows; Foraging mode/location: A = aerial, C = canopy, B = bark/bole, G = ground/low shrub; Nesting location: C = canopy/structural, V = cavity, G = ground/low shrub, B = Brown-headed Cowbird (a brood parasite); Habitat specificity: O = grassland obligate, F = grassland facultative, E = edge/open or disturbed, W = woodland; Migratory pattern: R = resident (year round), T = temperate migrant, N = neotropical migrant, X = exotic (non-native species); Dietary: O = omnivore, C = carnivore, G = granivore, I = insectivore.

Field Sparrow Lark Sparrow Grasshopper Sparrow Northern Cardinal Blue Grosbeak Indigo Bunting Painted Bunting Dickcissel Red-winged Blackbird Eastern Meadowlark Western Meadowlark Yellow-headed Blackbird Brewer’s Blackbird Common Grackle Great-tailed Grackle Brown-headed Cowbird Orchard Oriole Baltimore Oriole American Goldfinch House Sparrow

Species

APPENDIX A (Continued)

142 B. R. COPPEDGE ET AL.


143

Acknowledgments This work was supported by the USDA National Research Initiative Competitive Grants Program (Grant no. 9600853) and the Oklahoma Agricultural Experiment Station. This article is published with the approval of the director, Oklahoma Agricultural Experiment Station.

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